Practical Computing Skills for Omics Data (PLNTPTH 5004)
MCIC Wooster, Ohio State University
2025-08-26
Background in animal evolutionary genomics & speciation
In my free time, I enjoy bird watching – locally & all across the world
TBA
Name
Lab and Department
Research interests and/or current research topics
Something about you that is not work-related, such as a hobby or fun fact
Learning skills to:
Do your research more reproducibly and efficiently (e.g. by using code)
Work with large-scale “omics” datasets
TBD: explain focus on fundamental computation skills
Two related ideas:
Getting same results with an independent experiment (replicable)
Getting same results given the same data (reproducible)
Our focus is on #2.
“The most basic principle for reproducible research is: Do everything via code.”
—Karl Broman
Additionally, also important for reproducibility are:
Project organization and documentation (week 3)
Sharing your data and code (for code: Git & GitHub, week 4)
How you code (covered throughout)
Another motivator: working reproducibly will benefit future you!
Using code enables you to work more efficiently and automatically —
particularly useful when having to:
Do repetitive tasks
Recreate a figure or redo an analysis after adding a sample
Redo a project after uncovering a mistake in the first data processing step.
The next lecture will introduce omics data in a bit more details.
What this course does and does not focus on
While we’ll be using some example omics datasets, this course will not comprehensively cover the analysis of omics data — our focus is more on fundamental computational skills.
A highly recommended follow-up course to learn omics data analysis specifics:
Genome Analytics (HCS 7004) by Jonathan Fresnedo-Ramirez
Also: computational biology
TBA
Being able to work in the Unix shell is a fundamental skill in computational biology.
Bash (shell language)
VS Code
Good project organization & documentation is a necessary starting point for reproducible research.
You’ll learn best practices for project organization, file naming, etc.
You’ll learn how to manage your data and software
To document and report what you are doing, you’ll use Markdown files.
Markdown
Using version control, you can more effectively keep track of project progress, collaborate, share code, revisit earlier versions, and undo.
Git is the version control software we will use,
and GitHub is the website that hosts Git projects (repositories).
You’ll also use Git + GitHub to hand in your graded assignments.
Thanks to supercomputer resources, you can work with very large datasets at speed — running up to 100s of analyses in parallel, and using much larger amounts of memory and storage space than a personal computer has.
Using a workflow written with a workflow manager, you can run and rerun an entire analysis pipeline with a single command, and easily change and rerun parts of it, too.
DETAILS TBA
Address R vs Python
Be muted by default, but feel free to unmute yourself to ask questions any time.
Questions can also be asked in the chat.
Having your camera turned on as much as possible is appreciated!
“Screen real estate” — large/multiple monitors or multiple devices best.
Be ready to share your screen.
Books:
You can earn a total of 100 points across 6 assignments and 4 final project checkpoints.
These are due on Mondays and are worth 10 points each:
Plan and implement a small computational project, with the following checkpoints:
I: Proposal (due week 13 – 5 points)
II: Draft (due week 15 – 5 points)
III: Oral presentations on Zoom (week 16 – 10 points)
IV: Final submission (due Dec 15 – 20 points)
Data sets for the final project
If you have your own data set & analysis ideas, that is ideal. If not, I can provide you with this.
More information about the final project will follow later in the course.
Weekly readings — somewhat up to you when to do these, ideally before and after the lectures!
Weekly exercises — I recommend doing these on Fridays
Miscellaneous small assignments such as surveys and account setup.
Weekly materials & homework
I will try add the materials for each week on the preceding Friday — at the least the week’s overview and readings.
None of this homework had to be handed in.
We will have an optional but highly recommended weekly recitation meeting on Monday in which we go through the exercises for the preceding week.
Practice is key!
This course is intended to be highly practical and if you don’t practice the skills we will focus on by yourself, you will not get much out of it.
Please indicate your availability here: TBA
Homework: